Inverse numerical modeling for predicting kinetic rate constants in polyolefin pyrolysis based on product yield distribution for efficient plastic recycling.

The prediction of kinetic rate constants is a significant challenge in effective plastic pyrolysis recycling due to the wide range of generated byproducts, including char and aromatics. To address this challenge, an inverse numerical modeling methodology aimed at selective product distribution was formulated and assessed utilizing an established polyolefins reaction mechanism from existing literature to attain target yields of 50% oil and 50% gas within 60 min. This was accomplished by minimizing byproduct formation through an objective function designed to reduce the squared divergence between simulated and desired outputs, which was solved using an ordinary differential equation solver (ode23). The technique predicts rate constants to attain the desired fit, which was verified by experimental yields at 450 and 500 °C. Results indicate that inverse numerical modeling for precise estimation of kinetic rate constants markedly enhances the correlation between predicted and experimental yields, corresponding to a consistent yield trend by minimizing wax production at a reasonable scale throughout the processing time. The predicted rate constants suggest a 5% higher gas yield by eliminating wax up to 5% in line with maintaining the oil yield efficiency. Literature data support these findings and offer recommendations for enhancing experimental and statistical methodologies for predicting kinetic rate constants. This methodology provides a solid foundation for precisely predicting and optimizing product distributions in plastic pyrolysis across various temperature conditions, which could serve as an alternative and practical approach for predicting rate constants.